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Abstract

Introduction

Percent mammographic density (PMD) is a strong and highly heritable risk factor for
breast cancer. Studies of the role of PMD in familial breast cancer may require controls,
such as the sisters of cases, selected from the same 'risk set' as the cases. The
use of sister controls would allow control for factors that have been shown to influence
risk of breast cancer such as race/ethnicity, socioeconomic status and a family history
of breast cancer, but may introduce 'overmatching' and attenuate case-control differences
in PMD.

Methods

To examine the potential effects of using sister controls rather than unrelated controls
in a case-control study, we examined PMD in triplets, each comprised of a case with
invasive breast cancer, an unaffected full sister control, and an unaffected unrelated
control. Both controls were matched to cases on age at mammogram. Total breast area
and dense area in the mammogram were measured in the unaffected breast of cases and
a randomly selected breast in controls, and the non-dense area and PMD calculated
from these measurements.

Conclusions

The use of sister controls in case-control studies of PMD resulted in a modest attenuation
of case-control differences and risk estimates, but showed a statistically significant
association with risk and allowed control for race/ethnicity, socioeconomic status
and family history.

Keywords:

Mammographic density; case-control study; overmatching; case control

Introduction

Breast cancer is well known to cluster in families, which is thought to reflect inherited
susceptibility [1]. However, despite extensive research only 20% to 25% of the excess risk of breast
cancer in the first-degree relatives of women affected by the disease can be attributed
to mutations in known genes [2]. Much remains to be learned about why having a family history of the disease is a
risk factor for breast cancer. In previous work we have shown that variations in the
radiological appearance of the breast, referred to as mammographic density, were associated
with familial breast cancer [3].

Mammographic density varies among women of the same age and reflects differences in
breast tissue composition. Stroma and epithelium attenuate X-rays more than fat and
appear light on a mammogram, while fat appears dark [4]. The proportion of the mammogram occupied by radiologically dense tissue (percent
mammographic density (PMD)) is strongly associated with an increased risk of breast
cancer [5-7]. PMD varies with age, and among women of the same age according to height, weight
[11,12], parity [13,14], menopausal status [15] and menopausal hormone use [16], (reviewed in [8,9] but these factors explain only 20% to 30% of the observed variance in PMD). Twin
studies have shown that, after adjustment for these risk factors, additive genetic
effects account for about 60% of the variance in PMD [1]. Women with a first-degree relative diagnosed with breast cancer have on average
more extensive PMD than women of the same age with no family history. Furthermore,
average PMD increases with the number of first-degree relatives diagnosed with breast
cancer [10,11]. In previous work we found that PMD explained 14% (95% CI, 4 to 39%) of the association
of family history (at least one affected first-degree relative) with breast cancer
risk [3].

These findings suggest that PMD may play a role in familial breast cancer and that
studies of PMD might provide insight into the etiology of familial breast cancer.
In studies of familial breast cancer, the unaffected sisters of breast cancer cases
might be used as controls and have the advantage of matching on complex variables
such as family history, race/ethnicity and socioeconomic status [12-14], and perhaps age, which have all been associated with PMD and/or breast cancer risk.
In addition, sisters would be expected to be better matched for unmeasured environmental
risk factors than unrelated controls. However, the use of sister controls might also
result in overmatching, and attenuate the case-control difference seen in studies
using unrelated controls. The purpose of this study was to estimate the risks of breast
cancer associated with PMD using controls related to cases and unrelated controls,
and to compare the results obtained.

Methods

General method

We used mammographic images previously collected from three epidemiological studies
investigating the heritability and genetics of PMD. From these studies we had available
mammograms for at least two full sisters from a family, and an unrelated control.
We formed triplets comprised of an invasive breast cancer case, a sister control,
and an unrelated control, all matched according to age at the time of the mammogram.
Only original mammographic films were used in the analysis and we selected one craniocaudal
mammogram view from all participants, using the breast contralateral to the cancer
of cases, and a randomly selected side for controls. Ethics approval was obtained
from the University Health Network's Research Ethics Board and the Cancer Prevention
Institute of California's Research Ethics Board.

Study populations

Study participants were identified from three sources, including the Ontario and Northern
California sites of the Breast Cancer Family Registry (BCFR) [15], the Weekend to End Breast Cancer in Toronto (a fund-raising walk), and the Canadian
component of a twin study from which we randomly selected one twin [1].

The Breast Cancer Family Registry (BCFR) has been described in detail elsewhere [15]. The BCFR was established in 1995, with six participating sites from the USA, Canada,
and Australia ascertaining families either from population-based cancer registries
or from clinical settings. Population-based families were recruited by the Northern
California Cancer Center; from the province of Ontario, Canada; and from the metropolitan
areas of Melbourne and Sydney, Australia. Clinic-based families were recruited in
the USA by Columbia University, New York, the Fox Chase Cancer Center, Philadelphia,
and the Huntsman Cancer Institute at the University of Utah in Salt Lake City, Utah;
and in Australia by the University of Melbourne and New South Wales Cancer Council
in Melbourne and Sydney, Australia.

Population-based recruitment of incident cases of breast cancer reported to cancer
registries in Northern California and Ontario were used in the present research. Both
sites recruited cases and their family members selected according to age and the presence
of a family history of breast and other cancers. All participants completed the same
family history and epidemiology questionnaires and provided information on family
history of breast and other cancers and epidemiologic risk factors for breast cancer,
including height, weight, menopausal status and parity. All participants in addition
completed a food frequency questionnaire, and provided a blood sample from which DNA
was extracted. Informed consent was obtained from all participants for a larger study
[16], which included the current analysis.

Subject selection and data collection

Selection of cases

Cases were selected from the BCFR and were women with a personal history of unilateral
invasive breast cancer, for whom a mammogram prior to the cancer diagnosis was available.

Selection of controls related to cases

Sisters selected from the BCFR were matched to cases on age at mammogram and selected
if the mammograms were within five years of age and no later than up to one year from
the epidemiological questionnaire administration. In situations where there was more
than one unaffected sister in the family, the sister with the mammogram closest in
age to that of the case was selected.

Selection of unrelated controls

The unrelated controls were selected from a previous twin study [1] and the Weekend to End Breast Cancer. They were also individually matched to cases
based on age at mammogram screening and selected if the mammograms of the case and
unrelated control were within five years of age.

A total of 228 triplets, including 686 individuals, was available for analysis. Of
these, 179 case/sister pairs were from the Ontario BCFR, 49 case/sister pairs were
from the Northern California BCFR, 11 unrelated controls were from the Weekend to
End of Breast Cancer and 217 unrelated controls were from the twin study.

Classification of menopausal status

Menopausal status was classified according to reported age at cessation of menstruation
and the age at mammogram. If the age at mammogram was less than age at cessation of
menstruation, or the age at mammogram was less than one year greater than the age
at cessation of menstruation, the subject was classified as premenopausal. When the
difference between age at mammogram and age when menstruation stopped was 12 months
or more, the participant was classified as postmenopausal.

Mammographic density measurement

All mammograms were digitized using a Lumisys model 85 digitizer (Lumisys, Sunnyvale,
CA, USA) at a pixel size of 260 µm and 12 bits precision, and the digitized images
were measured by one observer (NFB). The case-sister-control sets were always in the
same read, and randomly distributed within that read. There was a total of eight reads
of 110 images, also containing the within and between reliability images. Reliability
was assessed both within and between reads using a 10% random selection of images
and was 0.97 and 0.79 for within and between reads respectively. Measurement of mammograms
has been described elsewhere [17]. Using the Cumulus 3 program (Canto, Berlin, Germany) an observer first marked the
outer and inner edges of the breast, from which total breast area was then calculated.
Using a thresholding tool, the observer outlined the dense area. The percentage of
total area that is dense, or PMD, and the non-dense area were calculated.

Statistical methods

The data analyzed consisted of three matched groups of 229 individuals, for a total
of 687 participants. Data analysis was carried out using SAS (version 9.2 for Windows;
SAS Institute Inc., Cary, NC, USA). The difference between PMD, dense area, non-dense
area, and total breast area for the cases and both control groups were assessed using
paired t-tests. We used Pearson correlation coefficient to examine the linear dependence of
mammogram measurements on covariates between the cases and both control groups, separately.
In addition, intraclass correlation coefficients (ICC) were calculated after adjustment
for age, body mass index (BMI), menopausal status (pre or post), parity (parous and
nonparous), hormone use (never, ever but not current, and current use) and case or
control status.

We calculated inter-quintile odds ratios (IQOR) and 95% confidence intervals (CI)
to assess the risk of breast cancer associated with square root transformed mammographic
measures using conditional logistic regression, with each mammographic measure as
a continuous variable. IQORs show the effect on breast cancer risk of change in transformed
mammographic measures from the lowest to the highest quintile, adjusted for age, weight
(kilograms), height (centimeters), parity, current menopausal hormone therapy (HT)
use and menopausal status. All statistical tests were two-sided and the significance
level was 0.05.

Results

Characteristics of subjects

Table 1 shows selected characteristics of the subjects. Cases, related controls and unrelated
controls were similar for most of the characteristics examined. Notwithstanding age
matching within five years, there were small but statistically significant differences
in age at the time of mammogram between cases and both related (-0.68 months; P <0.0001) and unrelated (-0.21 months; P = 0.0003) controls. Sister controls were more similar to cases in height, weight and
BMI than were unrelated controls. As a result of the method of selection of subjects
from the BCFR, all sister controls had a family history of breast cancer, and a family
history of breast cancer was reported by 48% of the cases and 23% of unrelated controls.
A slightly greater proportion of sister controls were postmenopausal (45.2%) compared
to cases and unrelated controls (both 44.7%). Ninety-two percent of the cases and
their sisters, and 93% of unrelated controls were white Caucasian.

Table 1. Descriptive statistics for case and control subjects, and for case-control paired
differences.

Comparison of mammographic measures between cases and controls

Figure 1 shows the distributions of PMD, dense area, non-dense area and total breast area,
in cases and the two control groups. Mean PMD was greatest in cases (34.7%), lower
in sister controls (mean PMD = 30.5%) and least in unrelated controls (mean PMD =
29.8%). Cases also had more extensive dense tissue (mean 44.6 cm2) than sister (mean 37.5 cm2) and unrelated (33.8 cm2) controls. Non-dense area was 94.4 cm2 in cases, 106.1 cm2 in sister controls, and 93.7 cm2 in unrelated controls. Total breast area was similar in cases (mean = 139.0 cm2) and sister controls (mean = 143.6 cm2) but was greater in cases than in unrelated controls (mean = 127.6 cm2).

Figure 1.Distribution of percent mammographic density, dense area, non-dense area and total
area for cases, sister controls, and unrelated controls. Shown are the means of the differences between cases and sister controls, and cases
and unrelated controls. P is a P value from the paired t-test, two-sided.

As shown in Figure 2, the unadjusted Pearson correlation coefficient (rpearson) for related case-control pairs showed a moderate correlation in PMD (r = 0.39, P <0.0001), dense area (r = 0.33, P <0.0001), non-dense area (r = 0.40, P <0.0001), and total breast area (r = 0.41, P <0.0001). The ICCs, adjusted for the factors shown in the Footnote to Figure 2, were all statistically significant but were smaller than the corresponding Pearson
correlations. The ICCs (adjusted for other risk factors) were 0.31 for PMD, and 0.27
for all the other comparisons.

Figure 2.Correlations of percent mammographic density, dense area, non-dense area and total
area between cases and sister controls, and cases and unrelated controls. r is a Pearson correlation coefficient.

For unrelated controls and cases, none of the correlations for PMD (r = 0.04, P = 0.54), non-dense area (r = 0.007, P = 0.91), and total breast area (r = 0.04, P = 0.28) were statistically significant. There was a weak positive and significant
correlation for dense area (r = 0.14, P = 0.03). The ICCs were similar to the Pearson correlations, but weak statistically
significant associations were seen for the dense area (ICC = 0.16, P = 0.01) and the total area (ICC = 0.14, P = 0.02), which may be chance findings.

Figure 3 shows correlations for measures of body size that are associated with variations
in PMD between cases and sister controls and between cases and unrelated controls.
Height was obtained by self-report and the distribution of values suggests that height
was reported with rounding to whole numbers.

Figure 3.Correlations of weight, height, and body mass index between cases and sister controls,
and cases and unrelated controls. r is a Pearson correlation coefficient.

We found significant correlations between cases and sister controls (P <0.001) for weight, height and BMI, but these measures were not significantly correlated
between cases and unrelated controls. The ICCs, adjusted for the factors shown in
the Footnote to Figure 3, were all statistically significant, and similar to the Pearson correlations for
cases and sister controls. ICCs comparing cases and unrelated controls were not statistically
significant.

Risk of breast cancer according to percent mammographic density and control group

Table 2 shows associations between square root transformed PMD and breast cancer risk, comparing
cases to sister controls and unrelated controls, adjusting for the risk factor shown
in the Footnote to the table. The coefficient for PMD (indicating the change in risk
of breast cancer associated with change in one (square root transformed) unit in percent
density) was 19% less for sister controls than for unrelated controls. The adjusted
IQOR for PMD was correspondingly smaller for sister controls (2.19: 95% CI: 1.20,
4.00) than for unrelated controls (2.62; 95% CI: 1.62, 4.25) but both confidence intervals
excluded unity. The analysis of the association of (square root transformed) dense
area with risk showed that the coefficient was 37% smaller when sister controls were
used but both control groups gave statistically significant associations of dense
area with risk of breast cancer. Non-dense area was inversely and significantly associated
with breast cancer when sister controls were used, but not with unrelated controls.

Table 2. Association of mammographic measures with risk of breast cancer when using sister
controls or unrelated controlsa

Mammograms in sisters were almost all carried out after the corresponding mammogram
in the case. Restriction of the analyses to those case-sister pairs where the mammogram
of the sister control was carried out after that of the case did not change the results
(data not shown) and provides no support for the hypothesis that mammographic density
in the sister control was influenced by changes in lifestyle prompted by the diagnosis
of breast cancer in the case.

Discussion

We carried out this study to determine if the risk of breast cancer associated with
PMD in a case-control study would differ when controls were related or unrelated to
the cases. Specifically, we sought to determine whether the selection of controls
related to cases would introduce 'overmatching' and attenuate estimates of breast
cancer risk associated with PMD. Our results showed expected correlations between
cases and sister controls for PMD and the dense and non-dense areas of the mammogram,
as well as for height, weight and BMI, all variables that are associated with PMD.
As expected, cases and unrelated controls in general showed no significant correlations
for these variables.

We have found that percent density is associated with breast cancer risk whether unrelated
or sister controls were used, with modest attenuation of effect when sister controls
were used. We think there are likely two principal reasons for these findings. First,
PMD is a very strong risk factor for breast cancer [5], and as shown here, the mean difference in PMD between cases and sister controls
and unrelated controls was only slightly smaller for sister controls than for unrelated
controls (4.2% and 4.9% respectively). Further, the adjusted correlation in PMD between
cases and sisters was modest (ICC = 0.31) and similar to the adjusted correlation
in PMD (0.28) previously seen between dizygous twin sisters [1]. In the absence of both of these features, it is likely that there would be greater
attenuation of the association of PMD with risk of breast cancer. Our results suggest
that these factors should be considered before using related controls in studies of
other phenotypes.

PMD is influenced by several factors that are also associated with breast cancer risk,
including age, menopausal status, race/ethnicity, and a family history of breast cancer.
When designing a study, controlling for some of these factors such as age and parity
is straightforward, while others, such as family history and socioeconomic status,
are more difficult. There are few suitable options for the selection of a control
group, and the two that were investigated here were the use of age-matched, unrelated
paired controls and a control group consisting of age-matched sisters of breast cancer
cases.

Our results suggest that sisters are suitable controls for case-control studies examining
factors associated with mammographic density. Coefficients and odds ratios for the
association of PMD with breast cancer showed evidence of modest attenuation when sister
controls were used, controlling for all covariates, although the confidence intervals
of the odds ratios overlapped substantially with those for unrelated controls. As
expected, correlations for height and weight were larger between cases and sister
controls than for unrelated control. BMI is known to be a negative confounder of the
effect of PMD with risk of breast cancer [18], and in these data adjustment for BMI had a larger effect than other covariates on
the risk estimates for unrelated controls (data not shown).

Conclusions

The use of sister controls in case-control studies of PMD resulted in a modest attenuation
of case-control differences and risk estimates, but showed a statistically significant
association with risk. These results are the consequence of the strong association
of the mammographic density phenotype with breast cancer and the modest correlation
in PMD between sisters. The use of sister controls for studies of mammographic density
has the advantage of controlling for race/ethnicity and family history of cancer with
little compromise in the case-control differences seen in PMD.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

LL carried out the design of the study, assisted in the analysis of the data and drafted
the manuscript.

LM assisted in the interpretation of the results and the revision of the manuscript.
QL, EH and SM performed the statistical analysis and assisted with data interpretation.
EJ and JR participated in the acquisition of data and the revision of the manuscript.
AP participated in the interpretation of the results and the revision of the manuscript.
NB conceived of the study design, made mammographic measurements, and participated
in the interpretation of the results. All authors participated in the drafting and
revision of the manuscript. All authors read and approved the final manuscript.

Authors' information

ADP holds a Canada Research Chair in the Genetics of Complex Diseases.

Acknowledgements

Funding was from the National Institutes of Health R01 CA102659. This work was also
supported by the National Cancer Institute, National Institutes of Health under RFA-CA-06-503
and through cooperative agreements with members of the Breast Cancer Family Registry
(BCFR) and Principal Investigators from Cancer Care Ontario (U01 CA69467) and the
Cancer Prevention Institute of California (U01 CA69417). The content of this manuscript
does not necessarily reflect the views or policies of the National Cancer Institute
or any of the collaborating centers in the BCFR, nor does mention of trade names,
commercial products, or organizations imply endorsement by the US Government or the
BCFR.